journal article
Open Access
Mar 16, 2024
Industry 4.0 and Smart Systems in Manufacturing: Guidelines for the Implementation of a Smart Statistical Process Control
Abstract
Digital transformations in manufacturing systems confer advantages for enhancing competitiveness and ensuring the survival of companies by reducing operating costs, improving quality, and fostering innovation, falling within the overarching umbrella of Industry 4.0. This study aims to provide a framework for the integration of smart statistical digital systems into existing manufacturing control systems, exemplified with guidelines to transform an existent statistical process control into a smart statistical process control. Employing the design science research method, the research techniques include a literature review and interviews with experts who critically evaluated the proposed framework. The primary contribution lies in a set of general-purpose guidelines tailored to assist practitioners in manufacturing systems with the implementation of digital, smart technologies aligned with the principles of Industry 4.0. The resulting guidelines specifically target existing manufacturing plants seeking to adopt new technologies to maintain competitiveness. The main implication of the study is that practitioners can utilize the guidelines as a roadmap for the ongoing development and implementation of project management. Furthermore, the study paves the way for open innovation initiatives by breaking down the project into defined steps and encouraging individual or collective open contributions, which consolidates the practice of open innovation in manufacturing systems.
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Details
- Published
- Mar 16, 2024
- Vol/Issue
- 7(2)
- Pages
- 24
- License
- View
Authors
Funding
CNPq
Award: 88887.343299/2019-00
CAPES
Award: 88887.343299/2019-00
Cite This Article
Lucas Schmidt Goecks, Anderson Felipe Habekost, Antonio Maria Coruzzolo, et al. (2024). Industry 4.0 and Smart Systems in Manufacturing: Guidelines for the Implementation of a Smart Statistical Process Control. Applied System Innovation, 7(2), 24. https://doi.org/10.3390/asi7020024
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